Spatial regression is a statistical technique used to analyze the relationship between variables while considering their spatial locations and dependencies. This method accounts for spatial autocorrelation, meaning that data points that are closer together may have more similar values than those that are farther apart. By integrating geographic information with traditional regression analysis, spatial regression helps in understanding patterns and predicting outcomes in various fields, including Earth Systems Science.
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